MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

A high-resolution study of the chromatin environment around regulatory elements

Author(s)
Metsky, Hayden C
Thumbnail
DownloadFull printable version (12.45Mb)
Other Contributors
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Manolis Kellis.
Terms of use
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582
Metadata
Show full item record
Abstract
Chemical modifications to histones, the proteins around which DNA wraps, are believed to play an important role in gene regulation. These modifications, along with others, make up a cell's "epigenome." It is known that the presence of a particular combination of these modifications at a region of a cell's genome determines, for that region, a state that carries functional significance. This work seeks to better understand the importance of not just presence, but also distribution of modifications within regulatory regions. One approach aimed at improving our understanding is to cluster regulatory regions based on information contained in signals that describe, at a high-resolution, the distribution of these modifications. In this thesis we develop a tool, called ChromSMS, to perform this clustering in a biologically meaningful and efficient way that is versatile in handling the underlying complexities of these signals. We apply the tool to data from the NIH's Roadmap Epigenomics Project to analyze ChromSMS and to better understand the mechanisms behind the patterns we observe. We find that ChromSMS produces meaningful clusters that are different from each other at a statistically significant level. Using ChromSMS to conduct analyses of epigenomic data, we discover strong relations between GC-content and the distribution of particular modifications. Furthermore, we uncover a small number of patterns that display high functional enrichment, and we begin to study the possible role and significance of motifs in driving these patterns. We conclude that ChromSMS can serve as a useful tool in examining regulatory regions at a high-resolution.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.
 
Cataloged from PDF version of thesis.
 
Includes bibliographical references (pages 111-114).
 
Date issued
2014
URI
http://hdl.handle.net/1721.1/100668
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

Collections
  • Graduate Theses

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.